Update on artificial intelligence against COVID-19: what we can learn for the next pandemic-a narrative review

被引:0
|
作者
Patil, Shankargouda [1 ]
Licari, Frank W. [1 ]
Bhandi, Shilpa [1 ]
Awan, Kamran H. [1 ]
Franco, Rocco [2 ]
Ronsivalle, Vincenzo [3 ]
Cicciu, Marco [3 ]
Minervini, Giuseppe [4 ]
机构
[1] Roseman Univ Hlth Sci, Coll Dent Med, South Jordan, UT USA
[2] Univ Roma Tor Vergata, Dept Biomed & Prevent, Rome, Italy
[3] Catania Univ, Dept Biomed & Surg & Biomed Sci, Catania, Italy
[4] Saveetha Univ, Saveetha Dent Coll & Hosp, Saveetha Inst Med & Tech Sci SIMATS, Chennai, Tamil Nadu, India
关键词
Artificial intelligence (AI); coronavirus diseases-19 (COVID-19); chest X-ray (CXR); diagnosis;
D O I
10.21037/jphe-23-139
中图分类号
R4 [临床医学];
学科分类号
1002 ; 100602 ;
摘要
Background and Objective: The coronavirus disease or coronavirus diseases-19 (COVID-19) is an ongoing pandemic that has created a tremendous public health concern. Apart from the reverse transcription polymerize chain reaction (RT-PCR), imaging findings play a crucial role in confirming its diagnosis and also constraining virus transmission. Artificial intelligence (AI) and its subsets have come to the rescue during these challenging periods and have been largely applied in managing the current COVID-19 pandemic. Role of AI in combating COVID-19 at different levels witnessed an enormous growth as documented in scientific literature. The present narrative review aims to illuminate the current state of evidence by providing an update on the use of AI during the COVID-19 pandemic in the year 2023 by assimilating the literature in identifying roles essayed by AI at different strata of COVID-19 expedition. Methods: English scientific articles were retrieved using Mesh terms-COVID-19, artificial intelligence with AND as Boolean operator in PubMed Database from January 2023 to December 2023 wherein AI essayed a role either in predicting, diagnosing, screening COVID-19 infection or any role essayed related to the condition. Abstracts, narrative or scoping reviews, systematic review, meta-analysis, comments, editorials were excluded. Data regarding the authors, the methodology with observations and inference as stated by the authors were retrieved and ponder upon to address the objectives of the study Key Content and Findings: Out of 1,661 articles obtained on initial search, 17 relevant articles were selected on application of the selection criteria. Scientific literature reveals that AI has contributed significantly by exhibiting precise, safe, and efficient imaging potential. Studies have also proposed various deep learning algorithms for the detection and treatment of COVID-19, for follow-ups, to evaluate patient response to treatment and so on. Conclusions: Thus, AI is swiftly evolving in the arena of healthcare. Further development of AI along with its subgroups can revolutionize public health care by reducing the work pressure on the front-line workers and be the backbone to improved management of a potential pandemic in the future.
引用
收藏
页码:1 / 11
页数:11
相关论文
共 50 条
  • [21] Governments and parliaments in a state of emergency: what can we learn from the COVID-19 pandemic?
    Bromo, Francesco
    Gambacciani, Paolo
    Improta, Marco
    JOURNAL OF LEGISLATIVE STUDIES, 2024,
  • [22] Pandemic considerations in pediatric critical care: what can we learn from COVID-19?
    Xiao, Tiantian
    Cheng, Ye
    Lu, Gouping
    Zhou, Wenhao
    TRANSLATIONAL PEDIATRICS, 2021, 10 (10) : 2875 - 2880
  • [23] Artificial Intelligence against COVID-19 Pandemic: A Comprehensive Insight
    Equbal, Azhar
    Masood, Sarfaraz
    Equbal, Iftekhar
    Ahmad, Shafi
    Khan, Noor Zaman
    Khan, Zahid A.
    CURRENT MEDICAL IMAGING, 2023, 19 (01) : 1 - 18
  • [24] Usage of Artificial Intelligence in the Combat against the COVID-19 Pandemic
    Fritsch, Sebastian
    Sharafutdinov, Konstantin
    Schuppert, Andreas
    Bickenbach, Johannes
    ANASTHESIOLOGIE INTENSIVMEDIZIN NOTFALLMEDIZIN SCHMERZTHERAPIE, 2022, 57 (03): : 185 - 197
  • [25] COVID-19 Pandemic: What Can the West Learn From the East?
    Shokoohi, Mostafa
    Osooli, Mehdi
    Stranges, Saverio
    INTERNATIONAL JOURNAL OF HEALTH POLICY AND MANAGEMENT, 2020, 9 (10) : 436 - 438
  • [26] What palliative care can learn from the COVID-19 pandemic
    Kelly, Daniel
    Dodds, Nigel
    INTERNATIONAL JOURNAL OF PALLIATIVE NURSING, 2020, 26 (06) : 261 - 262
  • [27] Pandemic Parallels: What Can Cybersecurity Learn From COVID-19?
    Furnell, Steven
    Haney, Julie
    Theofanos, Mary
    COMPUTER, 2021, 54 (03) : 68 - 72
  • [28] What can we learn about reshoring after Covid-19?
    Barbieri, Paolo
    Boffelli, Albachiara
    Elia, Stefano
    Fratocchi, Luciano
    Kalchschmidt, Matteo
    Samson, Danny
    OPERATIONS MANAGEMENT RESEARCH, 2020, 13 (3-4) : 131 - 136
  • [29] What can we learn about reshoring after Covid-19?
    Paolo Barbieri
    Albachiara Boffelli
    Stefano Elia
    Luciano Fratocchi
    Matteo Kalchschmidt
    Danny Samson
    Operations Management Research, 2020, 13 : 131 - 136
  • [30] COVID-19 and tourism: What can we learn from the past?
    Aronica, Martina
    Pizzuto, Pietro
    Sciortino, Caterina
    WORLD ECONOMY, 2022, 45 (02): : 430 - 444